Enhancement of Grid-Connected Photovoltaic Systems Using Artificial Intelligence


Book Description

​Enhancement of Grid-Connected Photovoltaic Systems Using Artificial Intelligence presents methods for monitoring transmission systems and enhancing distribution system performance using modern optimization techniques considering different multi-objective functions such as voltage loss sensitivity indexes, reducing total annual cost, and voltage deviation. The authors offer a comprehensive survey of distributed energy resources (DERs), explain the backward/forward sweep (BFS) power flow algorithm, and present simulation results on the optimal integration of photovoltaic-based distributed generators (PV-DG) and distribution static synchronous compensators (DSTATCOM) in different transmission and distribution systems. This book will be a valuable academic and industry resource for electrical engineers, students, and researchers working on optimization techniques, photovoltaic systems, energy engineering, and artificial intelligence.




Photovoltaic Systems


Book Description

This book provides comprehensive insight into the fault detection techniques implemented for photovoltaic (PV) panels. It includes studies related to predictive maintenance needed to improve the performance of the solar PV systems using Artificial Intelligence (AI) techniques. The readers gain knowledge on the fault identification algorithm and the significance of all such algorithms in real-time power system applications. Gives detailed overview of fundamental concepts of fault diagnosis algorithm for solar PV system Explains AC and DC side of the solar PV system-based electricity generation with real-time examples Covers effective extraction of the energy from solar radiation Illustrates artificial intelligence techniques for detecting the faults occurring in the solar PV system Includes MATLAB® based simulations and results on fault diagnosis including case studies This book is aimed at researchers, professionals and graduate students in electrical engineering, artificial intelligence, control algorithms, energy engineering, photovoltaic systems, industrial electronics.




Improvement of Grid-Connected Photovoltaic System Using Artificial Neural Network and Genetic Algorithm Under Different Condition


Book Description

Photovoltaic (PV) systems have one of the highest potentials and operating ways for generating electrical power by converting solar irradiation directly into the electrical energy. In order to control maximum output power, using maximum power point tracking (MPPT) system is highly recommended. This paper simulates and controls the photovoltaic source by using artificial neural network (ANN) and genetic algorithm (GA) controller. Also, for tracking the maximum point the ANN and GA are used. Data are optimized by GA and then these optimum values are used in neural network training. The simulation results are presented by using Matlab/Simulink and show that the neural network-GA controller of grid-connected mode can meet the need of load easily and have fewer fluctuations around the maximum power point, also it can increase convergence speed to achieve the maximum power point (MPP) rather than conventional method. Moreover, to control both line voltage and current, a grid side p-q controller has been applied.




Intelligent Renewable Energy Systems


Book Description

INTELLIGENT RENEWABLE ENERGY SYSTEMS This collection of papers on artificial intelligence and other methods for improving renewable energy systems, written by industry experts, is a reflection of the state of the art, a must-have for engineers, maintenance personnel, students, and anyone else wanting to stay abreast with current energy systems concepts and technology. Renewable energy is one of the most important subjects being studied, researched, and advanced in today’s world. From a macro level, like the stabilization of the entire world’s economy, to the micro level, like how you are going to heat or cool your home tonight, energy, specifically renewable energy, is on the forefront of the discussion. This book illustrates modelling, simulation, design and control of renewable energy systems employed with recent artificial intelligence (AI) and optimization techniques for performance enhancement. Current renewable energy sources have less power conversion efficiency because of its intermittent and fluctuating behavior. Therefore, in this regard, the recent AI and optimization techniques are able to deal with data ambiguity, noise, imprecision, and nonlinear behavior of renewable energy sources more efficiently compared to classical soft computing techniques. This book provides an extensive analysis of recent state of the art AI and optimization techniques applied to green energy systems. Subsequently, researchers, industry persons, undergraduate and graduate students involved in green energy will greatly benefit from this comprehensive volume, a must-have for any library. Audience Engineers, scientists, managers, researchers, students, and other professionals working in the field of renewable energy.




Artificial Intelligence for Solar Photovoltaic Systems


Book Description

This book provides a clear explanation of how to apply artificial intelligence (AI) to solve the challenges in solar photovoltaic technology. It introduces readers to new AI-based approaches and technologies that help manage and operate solar photovoltaic systems effectively. It also motivates readers to find new AI-based solutions for these challenges by providing a comprehensive collection of findings on AI techniques. It covers important topics including solar irradiance variability, solar power forecasting, solar irradiance forecasting, maximum power point tracking, hybrid algorithms, swarm optimization, evolutionary optimization, sensor-based sun- tracking systems, single-axis and dual-axis sun-tracking systems, smart metering, frequency regulation using AI, emerging multilevel inverter topologies, and voltage and reactive power control using AI. This book is useful for senior undergraduate students, graduate students, and academic researchers in areas such as electrical engineering, electronics and communication engineering, computer science, and renewable energy.




Enhanced Energy Harvesting in Grid Connected Photovoltaic Systems


Book Description

In "Enhanced Energy Harvesting in Grid-Connected Photovoltaic Systems," Kyrie Petrakis delves into the forefront of renewable energy technology, offering a comprehensive exploration of advanced strategies to optimize energy harvesting in photovoltaic (PV) systems. This groundbreaking book is an invaluable resource for engineers, researchers, and enthusiasts seeking to maximize the efficiency and sustainability of grid-connected solar power. Petrakis begins by providing a thorough understanding of conventional PV systems before navigating through cutting-edge enhancements. From novel materials and innovative design methodologies to intelligent control systems and real-time monitoring, the author unveils a spectrum of techniques to elevate the performance of grid-connected PV systems. Drawing on extensive research and practical insights, Petrakis elucidates the nuances of energy harvesting, storage, and distribution within the context of a smart grid. This meticulously crafted work not only elucidates the theoretical underpinnings of enhanced energy harvesting but also offers practical guidelines for implementing these advancements. With a balance of theoretical rigor and practical applicability, Kyrie Petrakis's "Enhanced Energy Harvesting in Grid-Connected Photovoltaic Systems" emerges as a beacon for ushering in a new era of sustainable and efficient solar energy utilization.




International Conference on Artificial Intelligence: Advances and Applications 2019


Book Description

This book introduces research presented at the “International Conference on Artificial Intelligence: Advances and Applications-2019 (ICAIAA 2019),” a two-day conference and workshop bringing together leading academicians, researchers as well as students to share their experiences and findings on all aspects of engineering applications of artificial intelligence. The book covers research in the areas of artificial intelligence, machine learning, and deep learning applications in health care, agriculture, business and security. It also includes research in core concepts of computer networks, intelligent system design and deployment, real-time systems, WSN, sensors and sensor nodes, SDN and NFV. As such it is a valuable resource for students, academics and practitioners in industry working on AI applications.




Design and Power Quality Improvement of Photovoltaic Power System


Book Description

This book presents a case study on a new approach for the optimum design of rooftop, grid-connected photovoltaic-system installation. The study includes two scenarios using different brands of commercially available PV modules and inverters. It investigates and compares several different rooftop grid-connected PV-system configurations taking into account PV modules and inverter specifications. The book also discusses the detailed dynamic MATLAB/Simulink model of the proposed rooftop grid-connected PV system, and uses this model to estimate the energy production capabilities, cost of energy (COE), simple payback time (SPBT) and greenhouse gas (GHG) emissions for each configuration. The book then presents a comprehensive small signal MATLAB/Simulink model for the DC-DC converter operated under continuous conduction mode (CCM). First, the buck converter is modeled using state-space average model and dynamic equations, depicting the converter, are derived. Then a detailed MATLAB/Simulink model utilizing SimElectronics® Toolbox is developed. Lastly, the robustness of the converter model is verified against input voltage variations and step load changes.




Smart Energy and Advancement in Power Technologies


Book Description

This book comprises peer-reviewed proceedings of the International Conference on Smart Energy and Advancement in Power Technologies (ICSEAPT-2021). The book includes peer-reviewed papers on renewable energy economics and policy, renewable energy resource assessment, operations management and sustainability, energy audit, global warming, waste and resource management, green energy deployment, green buildings, integration of green energy, energy efficiency, etc. The book serves as a valuable reference resource for academics and researchers across the globe.




Fault Analysis and its Impact on Grid-connected Photovoltaic Systems Performance


Book Description

A thorough and authoritative discussion of how to use fault analysis to prevent grid failures In Fault Analysis and its Impact on Grid-Connected Photovoltaic Systems Performance, a team of distinguished engineers delivers an insightful and concise analysis of how engineers can use fault analysis to estimate and ensure reliability in grid-connected photovoltaic systems. The editors explore how failure data can be used to identify how power electronics-based power systems operate and how they can help to perform risk analysis and reduce the likelihood and frequency of failure. The book explains how to apply different fault detection techniques—including signal and image processing, fault tolerant approaches—and explores the impact of faults in grid-connected photovoltaic systems. It offers contributions from noted experts in the field and is fully updated to include the latest technologies and approaches. Readers will also find: A failure mode effect classification approach for distributed generation systems and their components Explanations of advanced machine learning approaches with significant market potential and real-world relevance A consideration of the issues pertaining to the integration of power electronics converters with distributed generation systems in grid-connected environments Treatments of IoT-based monitoring, ageing detection for capacitors, image and signal processing approaches, and standards for failure modes and criticality analyses Perfect for manufacturers and engineers working in the power electronics-based power system and smart grid sectors, Fault Analysis and its Impact on Grid-Connected Photovoltaic Systems Performance will also earn a place in the libraries of distributed generation companies facing issues in operation and maintenance.